360-DQHM: A Phase-Topology-Based Memory Architecture Achieving O(1) Search Complexity at Billion-Entry Scale
Abstract
We present 360-DQHM (360-Dimensional Dynamic Quanta Hierarchical Memory), a holographic associative memory architecture based on a 360-dimensional complex-valued hypervector space. By encoding key-value pairs as phase-shifted superpositions within a single C^360 vector, the system stores up to 10^9 entries in only 2,880 bytes of memory while maintaining constant-time O(1) retrieval at 27-28 µs regardless of dataset size. On an AMD Ryzen 7 5700X CPU (no GPU), empirical evaluation across seven orders of magnitude (10^3 to 10^9) demonstrates 100% retrieval accuracy under the proposed Phase-Resonance Similarity metric.
Fields of Study & Subjects
Algorithms and Data Compression
Advanced Database Systems and Queries
Network Packet Processing and Optimization
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 9 March 2026
- Language
- EN
- Document type
- Preprint